Educational Science
M. Ghazavi; Saeed Bazzazian Bonab
Abstract
در مقاله حاضر، چگونگی یاد گیری درسهایی از جامعه مورچگان برای بهینهسازی مسائل مهندسی ارائه شده است و به عنوان یک مثال برای چنین مسائلی، دیوار حائل بتن مسلح در نظر ...
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در مقاله حاضر، چگونگی یاد گیری درسهایی از جامعه مورچگان برای بهینهسازی مسائل مهندسی ارائه شده است و به عنوان یک مثال برای چنین مسائلی، دیوار حائل بتن مسلح در نظر گرقته شده است که از نظر هزینهها میتواند بهینهسازی شود. روش طراحی سنتی برای دیوار حائل بتن مسلح، تنها با استفاده از روش سعی و خطا قادر به طراحی بهینه است. این مقاله، به معرفی یک روش بر مبنای یادگیری از مورچهها پرداخته شده است که اساساً یک روش جستجو برای مسائل بهینه سازی ترکیبی است و دارای پیچیدگیهای خاص است. این روش براساس مدل سازی ویژگیهای گروهی مورچهها و بالاخص ویژگی غذایابی آنها میباشد. این روش میتواند دیوارهای بتن مسلح را با توجه به دارا بودن قابلیت جستجو و استخراج جواب به صورت مؤثر از فضای جستجو، بهینهسازی کند. اساس تحلیل در این مقاله، تعیین کمترین وزن و کمترین هزینه برای طراحی دیوار حائل بتن مسلح است به طوری که در این طراحی، نیروی جانبی کل ناشی از فشار خاک پشت دیوار محاسبه شده و ملاحظات ظرفیت باربری، نشست، پایداری، و اصول طراحی سازههای بتن مسلح در نظر گرفته شده است. نتایج بدست آمده، گویای این مطلب می باشد که روش بهینه سازی بر اساس جامعه مورچگان می تواند مهندسین را در جهت به دست آوردن حداقل هزینه ساخت دیوارهای حائل به طور مؤثر آموزش دهد.
Education technology - Evaluation and testing
M.S. Amalnik
Abstract
This paper addresses the concept and development of an intelligent education system in concurrent engineering environment based on object oriented technique for conventional processes such as drilling, reaming, boring, slot drilling, end milling, tapping, etc. and unconventional processes such ...
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This paper addresses the concept and development of an intelligent education system in concurrent engineering environment based on object oriented technique for conventional processes such as drilling, reaming, boring, slot drilling, end milling, tapping, etc. and unconventional processes such as electrochemical machining (ECM), electro-discharge machining (EDM), electrochemical spark machining (ECSM), ultrasonic machining (USM) and wire-electro-erosion-dissolution machining (Wire-EEDM) for manufacturability evaluation and generation of alternative processes for improving product design. A feature based approach for acquiring design specification is used. Then the system automatically generates all possible alternative processes and estimates machining (cutting) cycle time, and cost, penetration rate, and efficiency for each process. The system works as a process of iterative redesign which suggests a way of using process information to find ways of reducing the cost of each design feature. It also estimates the optimum operation parameters for each process which balances between quality and manufacturing efficiency and to give designers immediate feedback about parameters such as the machining cycle time, cost and quality, efficiency and so on for optimization and give some advice to manufacturing engineers related to feed, speed, penetration rate, machining cycle time and cost saving.
Education technology - higher education
A.H. Monajemi; S. Masoudian; A. Estaki; N. Nematbakhsh
Abstract
Designing timetables, for example course timetables in an institute, is one of the most complicated and time-consuming challenges for personnel. Automating it, not only can help the personnel to manage their work better, but also can be considered as a desired sample to assess the ways of planning and ...
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Designing timetables, for example course timetables in an institute, is one of the most complicated and time-consuming challenges for personnel. Automating it, not only can help the personnel to manage their work better, but also can be considered as a desired sample to assess the ways of planning and to tackle the constraint satisfaction in artificial intelligence. In this paper, genetic algorithms are primarily studied and then it is applied for optimization of an imaginary faculty course timetable. The new designed algorithm is based on keeping the better chromosomes of the population and employing genetic operators on the others in order to improve the overall quality of genes. Some other amendments are also carried out to develop a more capable genetic algorithm for TT applications, compared to the standard one. According to the tests, the new GA algorithm will be more successful in generating high fidelity TTs which do not break any hard constraint. The proposed ideas, in this approach are applicable in other similar situations.
Architecture
S. Ali Mohammadi; F. Ali Moradi; E. Jabbari
Abstract
One of the most important pillars of optimized multi-purpose reservoir optimization models is the definition of a penalty or loss function. Due to the variety of operating goals and the complexity of the system, they often use alternative functions instead of using profit and cost functions, which only ...
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One of the most important pillars of optimized multi-purpose reservoir optimization models is the definition of a penalty or loss function. Due to the variety of operating goals and the complexity of the system, they often use alternative functions instead of using profit and cost functions, which only consider certain goals. These functions are the sum of several expressions that reflect the penalty or damages corresponding to the deviation from the desired values (needs). In this case, one of the most important steps in developing an optimization model is to determine the coefficients and capabilities (parameters) of these functions. This paper uses a dynamic stochastic programming (SDP) model to optimize the operation of a multi-purpose tank. With the help of this model, the parameters of the damage function have been evaluated through sensitivity analysis. For this purpose, the criteria of reliability, reversibility, and vulnerability have been used. Studies show that these parameters are much more sensitive to changes in the power of functions than the coefficients of functions.
TVET
A. Afshar; M. Shafie; O. Bozorg hadad
Abstract
By building large dams in different countries of the world, increasing the efficiency and effectiveness of these reservoir systems and maximizing the benefits of them is one of the most important issues studied in recent years. Evolutionary algorithms such as genetic algorithms (GA) are used in many ...
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By building large dams in different countries of the world, increasing the efficiency and effectiveness of these reservoir systems and maximizing the benefits of them is one of the most important issues studied in recent years. Evolutionary algorithms such as genetic algorithms (GA) are used in many scientific and engineering categories as search and optimization tools. Many applications of these methods have been reported on the issue of optimal utilization of reservoirs. In this research, an attempt is made to evaluate and evaluate the potential of new and applied formulations of genetic algorithm in solving engineering problems, to provide a new structure in order to optimize the operation of reservoirs using GA. In this study, new structures of the genetic algorithm are examined by performing different sensitivity analyzes and the best of them will be used to determine the optimal release of reservoir outflows. The results show that GA has the ability to provide good responses in the optimal use of reservoirs. Based on these results, the genetic algorithm with elitism, along with the two-point shear displacement operators and the low probability mutation, produces the best response. These results indicate the relatively good potential of genetic algorithms in solving large-scale problems that have complex objective functions.
